Data Scientist AI Products & Deployment

Job Title: Data Scientist – AI Products & Deployment

Department: Technology / Data Science 

Role Overview

Phillip Capital is seeking an experienced Data Scientist with a strong focus on AI product lifecycle management. The ideal candidate should have design and build advanced AI models and also possess the engineering rigor to deploy, scale, and maintain these solutions in both cloud-based and on-premise server environments. You will bridge the gap between data science research and production-grade software engineering.

Key Responsibilities

• AI Product Development: Design, develop, and validate machine learning and deep learning models tailored to financial and operational use cases.
• End-to-End Deployment: Own the deployment pipeline for AI models, ensuring seamless integration into existing systems via APIs, microservices, or embedded applications.
• Hybrid Infrastructure Management:
• Deploy and optimize models on major cloud platforms (e.g., AWS, Azure, GCP).
• Manage and secure model deployments on on-premise servers, ensuring compliance with data sovereignty and security protocols.
• Collaboration: Work closely with software engineers, DevOps teams, and business stakeholders to translate business problems into scalable AI solutions.
• Performance Optimization: Optimize model inference speed and resource utilization for both cloud and on-premise environments.

Required Qualifications

• Education: B.Tech in Computer Science, Data Science, Statistics, or a related field.
• Experience: 3+ years of experience in data science with a proven track record of shipping AI products to production.
• Technical Skills:
• Proficiency in Python, AI system design
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

Other optional skillsets :

• Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Experience with cloud AI services (AWS SageMaker, Azure ML, GCP Vertex AI).
• Experience deploying models on Linux-based on-premise servers (including containerization and orchestration).
• Soft Skills: Strong problem-solving abilities, attention to detail, and excellent communication skills for cross-functional collaboration.

Preferred Qualifications

• Experience in the financial services or fintech industry.
• Experience with CI/CD pipelines for machine learning models.
• Familiarity with edge AI or low-latency deployment scenarios.